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Atmospheric Chemistry and Climate

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Atmospheric Chemistry and Climate Powered By Docstoc
					Multi-model ensemble simulations of present-day and nearfuture tropospheric ozone
D.S. Stevenson1, F.J. Dentener2, M.G. Schultz3, K. Ellingsen4, T.P.C. van Noije5, O. Wild6, G. Zeng7, M. Amann8, C.S. Atherton9, N. Bell10, D.J. Bergmann9, I. Bey11, T. Butler12, J. Cofala8, W.J. Collins13, R.G. Derwent14, R.M. Doherty1, J. Drevet11, H.J. Eskes5, A.M. Fiore15, M. Gauss4, D.A. Hauglustaine16, L.W. Horowitz15, I.S.A. Isaksen4, M.C. Krol2, J.-F. Lamarque17, M.G. Lawrence12, V. Montanaro18, J.-F. Müller19, G. Pitari18, M.J. Prather20, J.A. Pyle7, S. Rast3, J.M. Rodriguez21, M.G. Sanderson13, N.H. Savage7, D.T. Shindell10, S.E. Strahan21, K. Sudo6, and S. Szopa16
1. University of Edinburgh, School of GeoSciences, Edinburgh, United Kingdom. 2. Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy. 3. Max Planck Institute for Meteorology, Hamburg, Germany. 4. University of Oslo, Department of Geosciences, Oslo, Norway. 5. Royal Netherlands Meteorological Institute (KNMI), Atmospheric Composition Research, De Bilt, the Netherlands. 6. Frontier Research Center for Global Change, JAMSTEC, Yokohama, Japan. 7. University of Cambridge, Centre of Atmospheric Science, United Kingdom. 8. IIASA, International Institute for Applied Systems Analysis, Laxenburg, Austria. 9. Lawrence Livermore National Laboratory, Atmos. Science Div., Livermore, USA. 10. NASA-Goddard Institute for Space Studies, New York, USA. 11. Ecole Polytechnique Fédéral de Lausanne (EPFL), Switzerland. 12. Max Planck Institute for Chemistry, Mainz, Germany. 13. Met Office, Exeter, United Kingdom. 14. rdscientific, Newbury, UK. 15. NOAA GFDL, Princeton, NJ, USA. 16. Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France. 17. National Center of Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO, USA. 18. Università L'Aquila, Dipartimento di Fisica, L'Aquila, Italy. 19. Belgian Institute for Space Aeronomy, Brussels, Belgium. 20. Department of Earth System Science, University of California, Irvine, USA 21. Goddard Earth Science & Technology Center (GEST), Maryland, Washington, DC, USA.

Background
• ‘OxComp’ model intercomparison for IPCC TAR sampled models in ~1999 • OxComp focussed on SRES A2 in 2100. • Models and emissions have developed in the last 5 years – time for an update • New scenarios from IIASA include AQ legislation measures (not in SRES) • SRES didn’t include ships – new datasets • SRES biomass burning(?) – new satellite data

Scope of IPCC-AR4
• Chapter 2: Changes in atmospheric constituents and in radiative forcing • Chapter 7: Couplings between changes in the climate system and biogeochemistry
– Includes a section on Air Quality

• Design intercomparison to be of direct use to IPCC-AR4

ACCENT IA3 / IPCC-AR4 modeling activities on climate / air pollution impact
Experiment 1: Delta O3 and radiative forcing 1850-2000-2100
Experiment 2: Air quality – climate interactions 2000-2030

Institute / model
Europe: Univ. L’Aquila, Italy ULAQ

CTM CCM trop.chem strat.chem

X

X

X

Univ. Oslo, Norway UIO_CTM2
CNRS/CEA, France LMDzINCA DLR, Germany DLR_E39C UK MetOffice, UK STOCHEM_HadGEM1

X
X X (X)

X
X X X

X
X (X)

Univ. Cambridge, UK UM_CAM
Univ. Edinburgh, UK STOCHEM_HadAM3 USA: NCAR, USA NCAR_MACCM Japan: JAMSTEC, Japan FRSGC_UCI JAMSTEC, Japan CHASER X X

X

X
X

X

X

X

X X X

(X) (X)

Gauss et al., ACPD, 2005

Radiative forcing due to changes in ozone since preindustrial times
-- A model study within ACCENT -M. Gauss1, G. Myhre1, I. S. A. Isaksen1, W. J. Collins2, F. J. Dentener3, K. Ellingsen1, L. K. Gohar4, V. Grewe5, D. A. Hauglustaine6, D. Iachetti7, J.-F. Lamarque8, E. Mancini7, L. J. Mickley9, G. Pitari7, M. J. Prather10, J. A. Pyle11, M. G. Sanderson2, K. P. Shine4, D. S. Stevenson12, K. Sudo13, S. Szopa6, O. Wild13, G. Zeng11
[1] Department of Geosciences, University of Oslo, Oslo, Norway [2] UK Met Office, Climate Research Division, Berks, United Kingdom [3] Joint Research Centre, Climate Change Unit, Ispra, Italy [4] Department of Meteorology, University of Reading, Reading, United Kingdom [5] Institut für Physik der Atmosphäre, DLR, Oberpfaffenhoffen, Germany [6] Laboratoire des Sciences du Climat et de L’Environnement, Gif-sur-Yvette, France [7] Dipartimento di Fisica, Università de L’Aquila, Coppito, L’Aquila, Italy [8] Atmospheric Chemistry Division, NCAR, Boulder, CO, USA [9] Division of Engineering and Appl. Sci., Harvard Univ., Cambridge, MA, USA [10] Earth System Science Department, University of California at Irvine, USA [11] Cambridge University, Chemistry Department, Cambridge, United Kingdom [12] Institute for Meteorology, University of Edinburgh, Edinburgh, United Kingdom [13] Frontier Research System for Global Change, Yokohama, Japan

Annually averaged zonal-mean ozone change (%) between 1850 and 2000 (emission change only!)

Climate-chemistry interactions
• Increased humidity
– ozone loss – ozone loss ozone ozone (mostly tropical LT) (middle stratosphere)

• Slow-down of gas phase ozone loss
• Increased PSC formation
– ozone loss ozone (high latitude LS)

• Increased Stratosphere-Troposphere Exchange / Lightning-NOx – ozone (UT) • Increase in tropopause height / convection / BD circulation – ozone (tropical LS)

Annual-mean ozone change (%) 1850 – 2000 (climate change only!)

Ozone column change Blue bars: chemical effect Red bars: climate effect

 Tropospheric change

Stratospheric change 

tropospheric change

-0.3

+1.3

Annual-mean radiative forcing (Wm-2) 1850 – 2000 (emission change only)

Chemical change

Chemical + Climate Change

RF due to ozone change between 1850 and 2000 [Wm-2]

Conclusions
• Increase in tropospheric ozone column, reduction in stratospheric ozone column since pre-industrial times … trop+strat combined: reduction in total ozone • RF due to tropospheric ozone change: +0.29 Wm-2 … +0.53 Wm-2 (CCMs, chemical change only) RF due to stratospheric ozone change: –0.10 Wm-2 … +0.08 Wm-2 (CCMs, chemical change only) … trop+strat combined: positive RF • Climate change: leads to an increase in total ozone since pre-industrial times in both the troposphere and the stratosphere. RFtrop gets larger, RFstrat smaller.

ACCENT IA3 / IPCC-AR4 modeling activities on climate / air pollution impact
Experiment 1: Delta O3 and radiative forcing 1850-2000-2100
Experiment 2: Air quality – climate interactions 2000-2030

ACCENT intercomparison (Expt. 2)
• Focus on 2030 – of direct interest to policymakers • Go beyond radiative forcing: also consider ozone AQ, Nand S-deposition, and the use of satellite data to evaluate models • Present-day base case for evaluation: Future changes – S1: 2000 in composition • Consider three 2030 emissions scenarios: related to – S2: 2030 IIASA CLE (‘likely’) emissions – S3: 2030 IIASA MFR (‘optimistic’) 1 year changes Future runs – S4: 2030 SRES A2 (‘pessimistic’) in composition • Also consider the effect of climate change: related to – S5: 2030 CLE + imposed 2030 climate climate change 5-10 year runs

Global NOx emission scenarios
200.0 160.0

SRES A2

120.0

CLE
80.0

40.0

MFR
0.0 1990 2000 2000 Europe Asia + Oceania Africa + Middle East SRES A2 - World Total 2010 2020 North America Latin America Maximum Feasible Reduction (MFR) SRES B2 - World Total 2030 2030

Figure 1. Projected development of IIASA anthropogenic NOx emissions by SRES world region (Tg NO2 yr-1).

Other emissions categories
• EDGAR3.2 ship emissions, and assumed 1.5%/yr growth in all scenarios • Biomass burning emissions from van der Werf et al. (2003) – assumed these remained fixed to 2030 in all scenarios • Aircraft emissions from IPCC(1999) • Modellers used their own natural emissions • Specified fixed global CH4 for each case (from earlier transient runs)

Requested model diagnostics
• Monthly mean, full 3-D
– – – – – O3, NO, NO2, CO, OH, … O3 budget terms CH4 + OH NOy, NHx and SOx deposition fluxes T, Q, etc. for climate change runs

• Daily NO2 column (GOME comparison) • Hourly surface O3 (for AQ analysis) • NETCDF files submitted to central database

26 Participating Models
• • • • • • • • • • • • • CHASER_CTM CHASER_GCM FRSGC/UCI GEOS-CHEM GISS GMI/CCM3 GMI/DAO GMI/GISS IASB LLNL-IMPACT LMDz/INCA-CTM LMDz/INCA-GCM MATCH-MPIC/ECMWF • • • • • • • • • • • • • MATCH-MPIC/NCEP MOZ2-GFDL MOZART4 MOZECH MOZECH2 p-TOMCAT STOCHEM-HadAM3 STOCHEM-HadGEM TM4 TM5 UIO_CTM2 ULAQ UM_CAM

CTMs driven by analyses CTMs coupled to GCMs CTMs driven by GCM output

NO3 wet deposition N. America

Mean model, all stations

All models, regional analysis

Dentener et al., in preparation

NO2 column comparison of GOME with model output [van Noije et al., in prep.]
Global spatial correlation KNMI-BIRA Harvard CHASER CTM2 FRSGC GEOS-CHEM GMI-CCM GMI-DAO GMI-GISS IMAGES IMPACT LMDz-INCA MOZ2G NCAR year 2 NCAR year 3 p-TOMCAT TM4 TM5 ULAQ 0.85 0.81 0.84 0.84 0.81 0.82 0.81 0.79 0.79 0.85 0.85 0.79 0.79 0.82 0.88 0.88 0.67 0.73 0.66 0.71 0.74 0.75 0.75 0.73 0.70 0.68 0.75 0.72 0.69 0.69 0.73 0.76 0.75 0.61 Bremen 0.88 0.86 0.87 0.84 0.81 0.81 0.81 0.82 0.80 0.88 0.88 0.83 0.83 0.90 0.88 0.88 0.75

NO2 column over

van Noije et al., in prep.

Analysis of O3 results
• Masked at tropopause using O3=150 ppbv • Interpolated to common vertical and horizontal grid • Ensemble mean model and standard deviations calculated • Compared to sonde measurements • Other ongoing validation work: NO2 columns, surface O3, CO, deposition fluxes • Global tropospheric O3 and CH4 budgets, radiative forcings

Year 2000 O3

Year 2000 Annual Zonal Mean Ozone (24 models)

Year 2000 Ensemble mean of 25 models Annual Zonal Mean

Annual Tropospheric Column

Sonde data from Logan (1999) + SHADOZ data from Thompson et al (2003)

Sonde ± 1SD
JFMAMJJASOND

Model ± 1SD

UT: 250 hPa MT: 500 hPa LT: 750 hPa

90-30S

30S-EQ

EQ-30N

30-90N

Ensemble mean model closely resembles ozone-sonde measurements

Year 2000 Inter-model standard deviation (%) Annual Zonal Mean

Annual Tropospheric Column

O3 in 2030, radiative forcing & influence of climate change

Multi-model ensemble mean change in tropospheric O3 2000-2030 under 3 scenarios
Annual Zonal Mean ΔO3 / ppbv

Annual Tropospheric Column ΔO3 / DU

‘Likely’
IIASA CLE SRES B2 economy + Current AQ Legislation

‘Optimistic’
IIASA MFR SRES B2 economy + Maximum Feasible Reductions

‘Pessimistic’
IPCC SRES A2 High economic growth + Little AQ legislation

Radiative forcing implications
Forcings (mW m-2) 2000-2030 for the 3 scenarios:
1500 1000
mW / m2

-23%

+37%

500 0 -500 CO2 CH4 O3

CO2 CH4 O3
CLE 795 116 63 MRF 795 0 -43 A2 1035 141 155

Impact of Climate Change on Ozone by 2030 (ensemble of 9 models)

Negative water vapour feedback

Positive stratospheric influx feedback

Mean - 1SD

Mean

Mean + 1SD

Positive and negative feedbacks – no clear consensus

Global budgets of O3 and CH4

Global O3 budget terms
O3 lifetime / days
Higher burden goes with longer lifetime Results for a single model, several scenarios

Colours signify different models

MFR Ensemble mean model (offset) Climate change shortens lifetime but burden can rise/fall

A2
As emissions rise, burden increases, lifetime falls

O3 burden / Tg(O3)

O3 budget and CH4 lifetime
O3 chemical loss / Tg(O3)/yr
Colours signify different models Climate change reduces CH4

Ensemble mean model (offset) Results for a single model, several scenarios IPCC TAR 8.4 years Models with longer CH4 have lower O3 destruction rates: EmissionsWhat causes the interhave O(1D) + H2O → 2OH minor influence model differences? on CH4 Water vapour?

Lightning NOx? Photolysis schemes?

CH4 lifetime / years

Conclusions
• Ensemble mean model O3 closely resembles observations • Inter-model standard deviations highlight where models differ the most • Quantitative assessment of 2030 scenarios provide clear options for policymakers (radiative forcing and AQ) • Influence of climate change uncertain • Global budgets reveal interesting and fundamental model differences • Analysis is ongoing – please come to meeting on Thursday night for more information. • dstevens@met.ed.ac.uk

Related Posters
• • • • • • • D155a Szopa et al. G186a Dentener et al. G190b Rast et al. G193 Gauss et al. G204 Van Dingenen et al. G205 Ellingsen et al. G210 Sudo & Akimoto


				
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